Theorem H.2 (Theorem 1.2 in [1]}) 

Let \(l\)  be a symmetric norm on \(\mathbb {R}^n\) . Any turnstile streaming algorithm (Definition REF )
that outputs, with probability at least \(0.99\) , a \((1\pm 1/6)\) -approximation for \(l(\cdot )\)  must use \(\Omega (\mathrm {mmc}(l)^2)\) 
bits of space in the worst case.

